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Analysis and simulation of an industrialvegetable oil refining process

ARTICLE in JOURNAL OF FOOD ENGINEERING · JUNE 2013

Impact Factor: 2.77 · DOI: 10.1016/j.jfoodeng.2013.01.034

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Gabriele Landucci

Università di Pisa

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Gabriele Pannocchia

Università di Pisa

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C. Nicolella

Università di Pisa

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Analysis and simulation of an industrial vegetable oil refining process

Gabriele Landucci a,⇑, Gabriele Pannocchia a, Luigi Pelagagge b, Cristiano Nicolella a

a Dipartimento di Ingegneria Civile e Industriale, Università di Pisa, Largo Lucio Lazzarino, 56126 Pisa, Italyb SALOV – Società Alimentare Lucchese Oli E Vini S.p.A. 1582, Via Montramito, San Rocchino 55054, Italy

a r t i c l e i n f o

Article history:

Received 10 August 2012

Received in revised form 1 November 2012

Accepted 27 January 2013

Available online 4 February 2013

Keywords:

Vegetable oil refining

Process simulation

Advanced thermodynamic models

Formation of flammable mixtures

a b s t r a c t

This work focuses on the performance analysis of an industrial vegetable oil refinery. Using a commercial

process simulator, a process model was developed and validated against actual vegetable oil refinery field

data. The simulator allowed investigating both energy and safety aspects related to the presence of resid-

ual extraction solvent (extraction grade hexane) in the processed crude vegetable oil. The critical nodes

for hexane accumulation in the process were evaluated, both considering ordinary operative conditions

and undesired process deviations due to increase of the hexane content. In this latter case, the control

actions able to restore the normal operation were simulated, in terms of increased utility consumption

(e.g., motive steam for ejectors and cooling water) or by modifying and optimizing equipment operating

conditions. Finally, the possibility of flammable mixtures formation inside process vent pipes, caused by

the entrainment of air due strong vacuum conditions, was also investigated.

2013 Elsevier Ltd. All rights reserved.

1. Introduction

Edible oil production by extraction processes greatly increased

in the last century due to both higher request and consumption

(FAO, 2011) and the progressive availability of more efficient pro-

cess technologies and equipment (Bockisch, 1998; Mielke, 1990;

Shahidi, 2005; Veloso et al., 2005; Calliauw et al., 2008; Cuevas

et al., 2009; Haslenda and Jamaludin, 2011; Szydłowska-Czerniak

et al., 2011; Zulkurnain et al., 2012). A critical phase of the edible

oil production chain is the final refining aimed at removing free

fatty acids, which, in too high concentrations, lead to the rancidity

of the oil (Cavanagh, 1976; Sullivan, 1976; Keurentjes et al., 1991;

Bhosle and Subramanian, 2005; Martinello et al., 2007; Calliauw

et al., 2008; Cuevas et al., 2009; Carmona et al., 2010; Akterian,

2011), and other minor components such as phospholipids, pig-

ments, proteins, oxidation products and the possible residual con-

tent of the solvent used for the extraction process. The main

operations involved in conventional refining for removing thementioned components are degumming, neutralization, washing,

drying, bleaching, deodorization and filtration (Gunstone et al.,

1994; Mag, 1990; Loft, 1990; Shahidi, 2005; Santori et al., 2012).

This stage of the production chain is crucial for the quality

enhancement of the final product.

Onethe more criticalaspectsof vegetable oil refining is relatedto

the presence of residual volatile solvent used for the extraction. In

particular, due to the low vapor pressure, the residual solvent may

cause a loss of efficiency in high temperature vacuum operations

(such as drying, bleaching and deodorization). In these operations,

vacuum conditions are often obtained by ejector systems (Bockisch,

1998; Mag, 1990; Loft, 1990; Muth et al., 1998; Akterian, 2011),

whose costs are mainly related to the consumption of steam and

cooling water for condensation. A possible increase of the residual

solvent concentration has a negative impact on these costs, besides

worseningthe environmental impact relateddue to higheremission

factors (odors, pollutant, etc.) (MRI, 1995; Muth et al., 1998).

Another criticality is due to the fact that the extraction solvent is

typically technical hexane (extraction grade hexane) (Dunford and

Zhang, 2003; MRI, 1995) a highly flammable liquid and vapor (GHS

hazard statement, Shell, 2012). In some critical nodes of the process,

the solvent accumulates in the vapor phase and mixing with air may

occur, potentiallyleadingto theformationof flammable mixturesand

confined explosion of the equipment in case of accidental ignition

(NFPA, 2007; Lees, 1996; Tugnoli et al., 2012). As reported in a previ-

ous work (Landucci et al., 2011) this mainly affects crude oil storage

tanks, as also experienced in two recent severe accidents which in-volved several fatalities (La Repubblica, 2006; El Economista, 2007).

Nevertheless, since very low pressure vacuum operations character-

ize several stages of the process (Bockisch, 1998; Mag, 1990; Loft,

1990; Shahidi, 2005; Muth et al., 1998; Akterian, 2011; Santori

et al., 2012), a low but significant amount of atmospheric air is en-

trained by seals or gaskets mixing with the process vents. This may

lead to the formation of flammable mixtures also in process lines.

Even if the vegetable oil refining process is well known, the

industrial facilities are continuously subjected to modifications,

revamping and new technologies implementation in order to

achievea higher process efficiency (Shahidi, 2005). In the literature,

several examples of simulation and experimental analysis of each

0260-8774/$ - see front matter 2013 Elsevier Ltd. All rights reserved.http://dx.doi.org/10.1016/j.jfoodeng.2013.01.034

⇑ Corresponding author. Tel.: +39 050 2217907; fax: +39 050 2217866.

E-mail address: [email protected] (G. Landucci).

Journal of Food Engineering 116 (2013) 840–851

Contents lists available at SciVerse ScienceDirect

Journal of Food Engineering

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single stage of the refining process are available (Keurentjes et al.,

1991; Wills and Heath, 2005; Zin, 2006; Ceriani and Meirelles,

2006; Didi et al., 2009; Farhoosh et al., 2009; Sampaio et al.,

2011), while a systematic performance analysis, which has been

extensively applied in the framework of process/chemical industry

(Motard et al., 1975; Shaw, 1992; Biegler et al., 1997; Vadapalli and

Seader, 2001; Hoyer et al., 2005; Towler and Sinnott, 2013) and

aimed at taking into account the mentioned critical aspects, is still

lacking.

The present analysis was therefore addressed at investigating

the vegetable oil refining process by the development of detailed

simulation model using the commercial software ‘‘Honeywell Uni-

Sim Design’’ (Honeywell, 2010a,b). The analysis was aimed at

identifying the main process streams, the reference substances,

and quantifying the mass and energy fluxes among the refining

plant. The process simulator was applied to case studies represen-

tative of the current industrial applications, deriving the input data

from inlet conditions of an actual vegetable oil refinery. In

particular, the vegetable oil refinery of SALOV S.p.A., located in

San Rocchino (Massarosa) (Italy), was considered in the analysis.

The simulation model was validated against actual field data of

the same plant and a sensitivity analysis was performed in order to

evaluate the utility consumption and potential safety relevant sit-

uations depending on the quality of the input feedstock, in partic-

ular evidencing the effect of the residual solvent content on the

whole process efficiency.

2. Materials and methods

2.1. Methodological approach

The flowchart of the methodology is reported in Fig. 1, and is

based on the approach followed in a previous work by Landucci

et al. (2011) for the analysis of crude vegetable oil storage systems.

The first step of the methodology was related to characteriza-

tion of the crude vegetable oil composition, which, for each typeof seed or fruit, is determined by environmental conditions during

plant grow and farming soil characteristics. A reference composi-

tion representative of different types of oil was used to perform

the further steps of the methodology. The second step (see Fig. 1)

consisted in the schematization of the typical process operations

for oil refining, with definition of operative conditions for process

equipment and evaluation of energy requirements (steam con-

sumption and other utilities). Then, a thermodynamic model was

applied in order to reproduce the vapor/liquid equilibrium of the

crude vegetable oil system (step 3 in Fig. 1), implementing the

presence of water and residual solvent content. The model was val-

idated against available experimental data.

Next (step 4 in Fig. 1), the refining process was simulated with

Honeywell UniSim Design. Specific subroutines were imple-

mented for the simulation of non-standard utilities such as the

ejectors used for keeping vacuum conditions in process vessels

and the deodorization operation.

The process simulator was used to perform the optimization of

operative conditions given the optimal composition of the feed-

stock, in order to minimize the costs related to utilities (step 5 in

Fig. 1). A sensitivity analysis was performed (step 6 in Fig. 1) aimed

at identifying the system response to the increasing residual sol-

vent content in the feedstock and possible restoration control mea-

sures. Finally, the possibility of formation of flammable mixtures

inside process lines was investigated (step 7 in Fig. 1).

2.2. Characterization of the crude vegetable oil

Crude edible oil is a complex multicomponent system. Recent

studies were focused on the detailed experimental or numerical

characterization of the vapor/liquid equilibrium of this system

(Christov and Dohrn, 2002; Rodrigues et al., 2004; Calliauw et al.,

2008; Ceriani et al., in press). Furthermore, advanced modeling

tools were implemented for the analysis of the refining process

taking into account different relevant triacylglycerols (TAGs), par-

tial acylglycerols (monoacylglycerols MAGs, diacylglycerols DAGs),

and the possible residual acid components, such as free fatty acids

of different type (Rodrigues et al., 2004; Farhoosh et al., 2009; Chi-

yoda et al., 2010; Silva et al., 2011; Sampaio et al., 2011; Gera-

simenko and Tur’yan, 2012; Teles dos Santos et al., in press;Ceriani et al., in press). Nevertheless, since the aim of the present

study was to evaluate the effect of residual hexane content on

the safety and energy performance of process equipment, a simpli-

fied reference composition was considered. The same approach

was followed in several studies on edible oil processing available

in the literature (Zhang et al., 2003; Ruiz-Mendez and Dobarganes,

2007; Cerutti et al., 2012).

The reference composition implemented in the simulation mod-

el is reported in Table 1. Such composition is based on the typical

crude sunflower oil feedstock used in SALOV S.p.A. vegetable oil

refinery, as already considered by Landucci et al. (2011). The oil

phase of the edible oil was schematized as pure triolein (reference

TAG), while the free fatty acids content is assumed as pure oleic

acid. Minor components such as sterols, tocopherols and squaleneare also present and were implemented in the UniSim Design list

of components as ‘‘hypo component’’ (Honeywell, 2010a). The hex-

ane residual content (schematized as pure n-hexane) was taken as

Characterization of the

crude vegetable oil

composition1

Thermodynamic modelfor the estimation of

vapor/liquid equilibrium3

Validation with

experimental data

Schematization of the oil

refining process2

Collection of typical

operations and

process conditions

from actual plants

Software implementation

of the refining process4

UniSim tool

Analysis of a case study

and optimization of

process conditions5

Sensitivity analysis6

Assessment of

utilities requirement

Set up of optimal

equipment operative

conditions

Increase of residual

solvent concentration

7 Safety aspects

Fig. 1. Flowchart of the methodology.

Table 1

Reference composition of the crude vegetable oil

considered in the present study based on SALOV

refinery data.

Components Mass fraction (%)

Triolein 97.29

Oleic acid 2.00

n-Hexane 0.10

n-C29H60 0.15

Sterols 0.40

Tocopherols 0.06

G. Landucci et al. / Journal of Food Engineering 116 (2013) 840–851 841

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elsewhere (Honeywell, 2010b), while Appendix A summarizes the

key parameters and equations used to predict enthalpy, entropy,

the fugacity coefficients for each component of the mixture and

thus the vapor/liquid equilibrium.

In order to test the validity of the model, a comparison with

available experimental data was carried out. A significant number

of literature studies focuses on vegetable oil/hexane mixtures at

high concentrations of hexane in the liquid phase (Fornari et al.,

1994; Ceriani and Meirelles, 2004; Smith and Florence, 1951), typ-

ical of extraction processes. The only available data for diluted

solutions, which are significant in the present case, are reported

by Smith and Wechter (1950). Data are referred to the soybeanoil/n-hexane solutions with a residual solvent content in the range

0.2–1.32% by weight. The hexane vapor pressure is measured in the

experiments as a function of the temperature. The model was fitted

on the experimental results by setting the triolein–hexane binary

interaction coefficient to 0.095 (Honeywell, 2010b). Notice that

for all other pairs of compounds, the default values of binary inter-

action coefficients were used. All binary interaction coefficients are

reported for completeness of exposition in Appendix A.

Fig. 3 reports a comparison between experimental data and val-

ues calculated with Unisim Design of n-hexane partial pressure in

the vapor phase as a function of temperature and hexane concen-

tration in the oil phase. As can be observed in this figure, the model

gives a quite accurate prediction with major deviations on the safe

side (e.g., 17% overprediction of n-hexane vapor pressure). The datawere linearly extrapolated for temperatures lower than 75 C asal-

ready performed in a recent publication (Landucci et al., 2011), in

which, however, the effect of water on the vapor phase composi-

tion was neglected and the model was set up only for the analysis

of storage conditions.

2.5. Simulation model implementation

The process simulation model, implemented in the UniSim

Design software, was aimed at evaluating the energy consumption

of the plant and the more critical nodes in which hexane is

accumulated, both in ordinary process conditions and following

unexpectedprocess deviations. Forthe sakeof brevityonly themain

issues related to vegetable oil refining simulator and innovative as-

pects connected with theanalysisof themore importantequipment

are summarized in the following sections. In order to highlight the

complexity of the developed process simulation model and the

potentialities of themethod, theSupplementaryinformation filere-

ports samples of the UniSim Design process flow diagrams (PFDs).

2.5.1. Condensers

The condensers are critical units under the point of view of

energetic efficiency of the process. These units are aimed at con-

densing the steam outlets from the ejectors connected to the main

process equipment to keep vacuum conditions (see specific

description in Section 2.5.3) by the use of cooling water available

in the refinery plant. Fig. 2 shows the condensers associated to

the ejector of the drying section (E5), bleaching (E6) and deodor-

ization (E7 for the first and second stage ejectors, E8 for the third

stage ejector). The sample UniSim Design PFD for the condenser

E5 is shown in Supplementary information.

The cooling water flowrate is the variable manipulated by the

software (ADJ 1 operator) which determines its value by imposing

a fixed temperature of 20 C for the condensate. This implementa-

tion allows for a better stability of the model in presence of input

deviations on the crude oil composition. The condenser parameters

were determined after a preliminary rating operation. The typical

range of cooling water flowrates, derived from actual plant design

data, was imposed in a preliminary dedicated simulation model to-

gether with the geometry documented in the equipment data-

sheets, thus calculating in the so-called rating mode an average

value for the pressure drops and heat transfer coefficient.

Then, condensers are implemented in the overall simulation

model by imposing thepressure drops on both tubes andshell sides,

and the product of the geometry area times the overall heat transfer

coefficient (‘‘designmode’’, see Honeywell (2010a) formoredetails).

This modeling approach was associated to the condensers E5,

E6 and E7 (see Fig. 2), while for condenser E8 a different approachwas followed. Since this unit receives the cooling water already

used in condenser E7, associated to ejectors EJ3a and EJ3b (see

Fig. 2), its modeling using an a priori fixed value for the overall

transfer coefficient may be inaccurate. In fact, the cooling water

is manipulated to satisfy specifications on other upstream units

and may vary significantly. Therefore, the so-called ‘‘rating mode’’

(see Honeywell (2010a) for more details on this procedure) was

used, in which one specifies the exchanger geometry (number/

dimensions/arrangements of tubes, shell passes, etc.) and appro-

priate correlations are internally used to evaluate the heat transfer

coefficients and pressure drops on the basis of actual flowrates.

2.5.2. Deodorization column

The deodorization stage is aimed at removing minor compo-nents (e.g., squalene and polycyclic aromatic compounds) which

cause odor and the loss of quality of the final product. The deodor-

ization column (C1 in Fig. 2) is a stripping column made of five

chambers, each fed with low pressure steam (LPS, at 1.5 bar). The

total LPS mass flowrate is set as the 1.8% of the total refined oil

flowrate. The hot exhausted vapors from each chamber are col-

lected and fed to a water scrubber (C2 in Fig. 2), where the fatty

acids are removed and purged.

In order to reach the requiredstrong vacuum conditions (in par-

ticular, 0.2 kPa pressure and temperature higher than 220 C) the

ejector system depicted in Fig. 2 is required.

The column was modeled in the UniSim Design software by

implementing six separators in series, aimed at representing the

five chambers of the column C1 plus the bottom of the column,in which the separation is also carried out thus reaching the

Table 2

Operative conditions of the main sections of the refining process.

Process section Operative temperature (C) Operative pressure (kPa)

Neutralization 20 100

Degumming 60–70 100

Washing 90 100

Drying 90 5

Bleaching 105 6

Deodorization 230 0.2

Fig. 3. Validation of the thermodynamic model developed in UniSim Design. HEX:

residual hexane content in thecrudevegetable oil(% by weight basis).Experimentaldata were derived from Smith and Wechter (1950).


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vapor/liquid equilibrium conditions. For the first four separators an

energy stream is added in addition to the LPS stripping stream in

order to simulate the presence of high pressure steam (saturated

steam at 40 bar) fed to internal heating coils inside the C1 column

chambers in order to keep high temperature conditions. The Uni-

sim Design PFD is reported in Supplementary information.

2.5.3. Ejectors

Several steam driven ejectors are used in the refinery to obtain

the needed vacuum conditions in the process equipment. As evi-

denced in Section 2.5.1 these pieces of equipment are critical for

the energy performance assessment of the refinery plant. However,

no dedicated model is available in the process simulator for ejec-

tors. Thus, a specific modeling tool was implemented in the soft-

ware in order to achieve an accurate performance evaluation

exploiting the UniSim Design software ‘‘User Unit Operation’’

function. The function allows inserting the data derived from ac-

tual ejector systems datasheets, in particular the design curves.

These curves report the entrainment ratio (1/l), given by the suc-tion flow related to air at 20 C respect to the motive steam flow, as

a function of the ratio between the discharge and suction pressures

(P d/P s). The curves vary according to the parameter given by the ra-

tio between suction and motive steam pressures (P s/P m). The anal-

ysis of the design curves and optimization of ejector systems is

extensively described in the technical literature (Meherwan,

1999; Akterian, 2011).

Hence, by setting the pressures of the equipment in vacuum

conditions (e.g., P s), of the motive steam (e.g. P m) and of the dis-

charge (P d) it is possible to derive by reading on the curves the

entrainment ratio and calculating the necessary mass flows as

follows:

1

l¼ maMS

1

K ejð1Þ

where ma is the entrained flow of air at 20 C, MS is the flow of mo-

tive steam and K ej is a correction factor for suction flows other than

air, expressed as follows:

K ej ¼

ffiffiffiffiffiffiffiffiffiffiRS T S RLT L

s ð2Þ

where RS is the gas constant of suction flow, RL the gas constant of

air (=287 J kg1 K1), T S the temperature (in K) of suction flow, T Lthe reference air temperature for the ejector (=293 K).

Table 3

Fitting parameters for the approximation of the ejectors

design curves (see Eq. (3)).

Parameter (P s/P m) X 1 X 2

0.001 4.14 0.983

0.002 3.81 0.910

0.005 3.38 0.732

0.010 3.03 0.673

0.020 2.70 0.615

0.050 2.26 0.489

Table 4

Comparison between the process parameters evaluated by the model and the available field data. For tags locations, see Fig. 4.

TAG Description Units Model results Field data

FI1 Refined oil exit flow kg/h 14,558 14,075

PI1 Pressure in the deodorization column kPa 0.2 0.22

TI1 Temperature of the bleaching reactor C 104.8 110.1

TI2 Temperature of crude oil at the deodorization inlet C 231.7 230.7

TI3 Refined oil exit temperature C 160.9 154.8

TI4 Temperature of the deodorization column top side C 135.8 153.0

Drying

Bleaching

Deodorization

Crude oil from

neutralization

Refined oil

to storage

2

3

4

1

CW1

CW2

CW3

CW4

CW5

CW6

H1 H2 H3Bleaching

earth &

activated

carbon

5

C1 C2 V1

C3 V2

C5 V3E5 E6

H4 H5 H6 E2

H7 H8 H9 E3 E4

W1

E1

W2

LEGEND:

C

CW

E

H

V

W

Condensed steam

Cooling water

Energy stream

Low or medium pressure steam

Vent

Process waste

Material stream tag

C4

E7

Fig. 4. Schematic representation of the heat and material balance on the analyzed plant sections.

844 G. Landucci et al. / Journal of Food Engineering 116 (2013) 840–851

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In order to obtain more realistic results, the actual datasheet of

industrial ejector systems were obtained (Körting Hannover AG,

1994) inserting in the UniSim Design software ‘‘Unit Operation’’

function the numerical interpolation of the design chart curves

as follows:

maMS

¼ X 1P d=P s

X 2ð3Þ

where X 1 and X 2 are fitting constants reported in Table 3 for differ-

ent values of the parameter P s/P m.

In the process simulator, for each equipment operating in vac-

uum conditions the suction temperature, the suction pressure

and the motive steam pressure are specified as input parameters;hence the software applies Eqs. (1)–(3) to evaluate the motive

steam flow which is necessary to keep an imposed discharge

pressure.

Therefore, by varying the input conditions, e.g. due to devia-

tions in the process (in particular, the increase of volatile com-

pounds affect the suction flow), the energetic consumptions are

evaluated by calculating the necessary motive steam flow needed

to restore the optimum process conditions.

3. Results and discussion

3.1. Model validation and case study analysis

In order to validate the process simulator, actual field data werederived from SALOV S.p.A. refinery during typical working

Table 5

Heat and material balance on the plant sections analyzed in the present study. For the identification of the streams, refer to Fig. 4. Composition is expressed in percentages by

weight basis.

Item Material streams

1 2 3 4 5b W1 W2

Temperature (C) 90.0a 84.3 105.2 20.0a 25.0a 105.0 48.4

Pressure (kPa) 195.0 200.0a 210.0a 186.0 200.0a 8.0 0.2

Flowrate (kg/h) 14,887.5 14,795.2 14,695.0 14,558.4 14.8 97.8 133.0a

Triolein (%) 98.14 98.74 98.75 99.62 0.0 100.0 5.2

Water (%) 0.55 0.01 0.01 0.0 100.0 0.0 0.0

n-Hexane (%) 0.10 0.02 0.01 0.0 0.0 0.0 67.3

Oleic acid (%) 0.60 0.61 0.61 0.0 0.0 0.0 0.0

Other (%) 0.61 0.62 0.62 0.38 0.0 0.0 27.5c

a Value imposed to process simulator.b The stream containing bleaching earth and activated carbon is modeled as pure water.c Spent bleaching earth.

Table 6

Heat and material balance on the plant utilities. For the identification of the streams, refer to Fig. 4. C = steam condensate; CW = cooling water; E = energy stream; H = steam;

V = vent.

ID Physical

state

Description Thermal power

(kW)

Flowrate

(kg/h)

Temp.

(C)

Pressure

(kPa)

Drying sectionC1 Liquid Steam condensate associated to ejector EJ1a 150.1 19.0 16.5

C2 Liquid Steam condensate associated to ejector EJ1b 1153.0 127.5 250.0

CW1 Liquid Cooling water fed to the drying section condensers 9282.0 8.0 150.0

CW2 Liquid Cooling water exiting the drying section condensers 9282.0 18.0 149.9

H1 Vapor Motive steam fed to first stage ejector EJ1a 70.1 175.5 900.0

H2 Vapor Motive steam fed to second stage ejector EJ1b 53.4 175.5 900.0

H3 Vapor Drying steam pre-heating in E1a 1153.0 127.5 250.0

V1 Vapor Vent exiting from drying section 70.6 123.2 108.0

E1 – Heat removed in downstream degumming section with heat exchanger 142.0

Bleaching section

C3 Liquid Steam condensate associated to ejector EJ1a 301.0 127.5 250.0

C4 Liquid Steam condensate associated to ejector EJ1b 30.4 19.8 16.5

CW3 Liquid Cooling water fed to the bleaching section condensers 1180.8 8.0 150.0

CW4 Liquid Cooling water exiting the bleaching section condensers 1180.8 20.0 150.0



H6 Vapor Bleaching steam pre-heating in E1b 301.0 127.5 250.0V2 Vapor Vent exiting from bleaching section 35.4 134.0 108.0

E2 – Bleaching pre-heating 11.0

Deodorization section

C5 Liquid Steam condensate associated to ejector EJ3 1537.0 19.8 102.5

CW5 Liquid Cooling water fed to the deodorization section condensers 240,000.0 8.0 150.0

CW6 Liquid Cooling water exiting the deodorization section condensers 240,000.0 12.0 140.9



H9 Vapor Motive steam fed to third stage ejector EJ3c 26.0 175.5 900.0

V3 Vapor Total ventflowrateexiting from deodorization section condensers (E7 and

E8)

33.8 132.4 108.0

E3 – C1 chambers external coil heating 89.0

E4 – Steam (40 bar) for oil preheating 448.0

E5 – Cooling of scrubber C2 recycle 53.0

E6 – Air cooler 1055.0

E7 – Cooling unit 163.0


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deodorization. Both steam and cooling water utilities have the

highest requirements in order to keep the severe operative condi-

tions imposed by the process. In particular, low pressure (0.2 kPa)

leads to major motive steam consumption and associated cooling

water for condensation, while the high operative temperature of the column (230 C) is kept also by the use of additional heating

(energy streamE4 in Table 6) carried out with high pressure steam.

Besides, additional heat exchangers are needed for cooling the

scrubber C2 (see Fig. 2) recycle and the vents before the treatment

and the discharge in the atmosphere.

3.2. Process optimization and sensitivity analysis

The analysis of the refinery in the baseline case (0.1% hexane by

weight basis in the inlet crude oil) highlighted the criticalities re-

lated to the energy consumptions in the refinery lowpressure units

(e.g., drying, bleaching and deodorization). Since the ejector sys-

tems operative conditions affect the whole refinery energetic per-formance, the process simulator was applied in order to optimize

the operating conditions for the minimization of motive steam

consumption. The optimization was carried out on the three ejec-

tor systems considering that the motive steam is available in the

plant at the same pressure (medium pressure steam, MPS at 9 bar).

Fig. 5a reports an example of optimization, in particular related

to the ejector system connected to the drying flash drum (EJ1a/b

with condenser E5, see Fig. 2). As can be seen in the scheme, the

ejector is constituted by two different sections in which P s

is the

suction pressure, representative of the equipment operative

conditions, P out the system discharge pressure, MSA and MSB the

motive steam streams respectively for the first and second stage,

and P int is the intermediate pressure, which is the degree of free-

dom (DOF) to specify for the optimization. The optimization is car-

ried out by varying both MSA and MSB and finally obtaining the P intwhich minimizes the overall steam consumption (e.g., the sum of

MSA and MSB), as shown in Fig. 5a. Determining the intermediate

ejectors pressure allows for the process energetic efficiency

enhancement.

The described optimization method can be performed also by

considering a possible increase of the inlet residual hexane con-

tent, as reported in Fig. 5b. In particular the figure shows the opti-

mized intermediate pressure for all the considered ejector systems

(see Fig. 2 for tags and equipment representation). These outcomes

might be potentially applied when a different feedstock quality is

accepted and processed by the refinery for a mid- or long-term

period, with the need of a systematic improvement of the operat-

ing conditions. As shown in Fig. 5b, the increase of the residual

hexane content has a stronger influence on the drying and bleach-

ing sections respect to the deodorization, since in these sections

the major part of hexane is removed (see Section 3.1). This results

in the increase of the intermediate pressure for optimizing the mo-

tive steam consumption.

The results of the sensitivity analysis carried out by varying the

inlet hexane concentration and optimizing the operating condi-

tions and process variables are reported in Table B1 of Appendix

B. The table allows determining the optimized operating condi-

tions referring to the base case discussed in Section 3.1.On the basis of the sensitivity analysis results, the overall utili-

ties requirements were derived and shown in Fig. 6. Fig. 6a shows

the increase of the overall motive steam and cooling water con-

sumption by varying the inlet hexane concentration of one order

of magnitude (e.g., ranging from 0.1% to 1.5% by weight basis). Mo-

tive steam consumption is increased by 40%, showing a more sig-

nificant variation respect to cooling water utility, which increase

is limited to 1%. This is due to the fact that the highest flowrate

of cooling water is a fixed simulation parameter, since it is fed to

the condenser of the third ejector (EJ3c, see detailed description

of simulation set up in Section 2.5.1). This flowrate is almost

twenty times higher than the sum of the other cooling water util-

ities, which can be varied in order to control the condensate tem-

perature (see Section 2.5.1).In order to determine the variation in the process vents behav-

ior due to the increase of inlet hexane concentration, Fig. 6b pre-

sents the change in the hexane removal percentage (thus,

starting from the values evaluated at 0.1% residual hexane content,

see Section 3.1) in each process section. The results highlight that

the excess hexane is mainly removed in the drying section, due to

the oversizing of the equipment. Hence, this allows decreasing the

hexane amount fed to the downstream units, which hexane re-

moval decreases as shown in Fig. 6b.

Therefore, the sensitivity analysis allowed determining the

change in process parameters and utility requirements for restor-

ing the process operating conditions given unforeseen changes of

the inlet feedstock. It clearly appears that the increase of volatile

solvent residual has a negative impact on the energetic costs of the refining process.

Fig. 7. Comparison between the flammability range of hexane considering two

inert reference gases (carbon dioxide and nitrogen) and vapor concentration in the

venting line for (a) drying, (b) bleaching and (c) deodorization considering a

residual hexane content of 0.1% by weight basis in the inlet crude oil. For air

infiltration types characterization, see Table 7.


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3.3. Formation of flammable mixtures inside process streams

The process simulator pointed out the more critical nodes for

hexane accumulation, also considering the potential variation of

the initial hexane residual in the process feed. Among the possi-

ble hazards related to the presence of hexane inside process

pipes, one of the critical issues is related to the possibility of

air entrainment from gaskets and seals in strong vacuum operat-

ing pipes, thus leading to the formation of flammable mixtures

in confined spaces. This might lead to fire and explosion hazards

in case of accidental ignition of the flammable mixture, already

highlighted for the storage equipment in a previous work (Land-

ucci et al., 2011).

Therefore, the process simulator was employed to investigate

this problem, considering an additional air flow in the three vent

lines (V1, V2 and V3, see Fig. 4) given a reference air entrainment

value, specified by the ejector manufacturer (Körting Hannover

AG,1994) for the vent discharge line. Table 7 reports the considered

entrainment value (infiltration type 2), also considering a possible

negative or positive variations respect to this reference value

(respectively, infiltration types 1 and 3 in Table 7).

Fig. 7 reports the evaluated residual hexane concentration in

the vent lines evidencing the possibility of formation of flammable

mixtures in the drying (Fig. 7a), bleaching (Fig. 7b) and deodoriza-

tion (Fig. 7c) sections as a function of the different air entrainment

rates given a fixed hexane residual content in crude oil feed (e.g.,

0.1% by weight basis). A flammable mixture is potentially formed

if the calculated concentration point enters inside the flammable

range, i.e. the region of the chart included inside the reference con-

tinuous lines. In absence of data for water as inerting fluid, the ef-

fect of nitrogen (bright lines in Fig. 7) and carbon dioxide (dark

lines in Fig. 7) as diluents was taken into account in order to obtain

preliminary indications for the methodology (Mashuga and Crowl,

1998; Zabetakis, 1965). Furthermore, the flammability range is af-

fected by operative pressure and temperature, but the use of data

referred to 25 C temperature and 1.01 bar allows for evaluation of

the flammability hazards on the safe side in the considered process

sections (Lees, 1996).

The results make clear that in the case of higher hexane concen-

tration in the vent line, the entrained air is not sufficient to form

flammable mixtures, thus leading to a less hazardous situation.

This is the case of the drying section, in which the major part of

hexane is removed and, as shown in Fig. 7a, and in which none

of the calculated points fall under the flammable region even for

high air entrainment rates. On the contrary, for the other two sec-

tions, the hexane vent content is lower and some points calculated

for high air entrainment rates especially in the deodorization sec-

tion vent (see Fig. 7c), fall into the hazardous zone. This evidences a

safety criticality for strong vacuum operating equipment in pres-

ence of flammable vapors.

Hence, this type of hazard might be taken into account during

the vent pipeline design and in maintenance operations.

Table A1

Main parameters and equations implemented in the thermodynamic model ( Honeywell, 2010b).

ID Equation Description Parameters

Eq. (1) P ¼ RT V b a

V ðV þbÞþbðV bÞ Peng–Robinson state equation P = Pressure (Pa)

R = 8314(J kmol1 K1) universal gas

constant

T = Temperature (K)

V = Volume (m3)

a = see Eq. (6)b = see Eq. (5)

Eq. (2) Z 3 - ( 1 - B) Z 2 + ( A - 2B - 3B2) Z - ( AB - B2 - B3) = 0 Peng–Robinson expressed in terms

of the compressibility factor Z

Z = Compressibility factor = (PV)/

(RT)

A = see Eq. (3)

B = see Eq. (4)

Eq. (3) A = aP /(RT )2 Parameter in Eq. (2) a = see Eq. (6)

Eq. (4) B = bP /(RT )2 Parameter in Eq. (2) b = see Eq. (5)

Eq. (5) b ¼ PN

i¼1 xibi ; bi ¼ 0:077796RT c ;iP c ;i

1st Peng–Robinson equation

coefficient for mixtures

xi = mass fraction of the ith

component of the mixture of N

components.

T c ,i = critical temperature of the ith

component

P c ,i = critical pressure of the ith

component

Eq. (6) a ¼ PN

i¼1

PN j¼1 xi x jðaia j Þ

0:5ð1 kijÞ; ai ¼ ac ;iai

ac ;i ¼ 0:457235ðRT c ;i Þ

2

P c ;i; a0:5i ¼ 1 þ mið1 T

0:5r ;i Þ

2nd Peng–Robinson equation

coefficient for mixtures – original

formulation

T r ,i = T /T c ,ikij = system specific experimental

binary interaction factor

mi = see Eq. (7)

Eq. (7) mi ¼ 0:37464 þ 1:5422xi 0:26992x2i ; xi 6 0:49

mi ¼ 0:379642 þ ð1:48503 ð0:164423 0:016666xiÞxiÞxi ; xi > 0:49

Polynomial factor for Eq. (6) –

original formulation

xi = Acentric factor of the ithcomponent

Eq. (8) ai ¼ T N i=ðM i 1Þr ;i expðLið1 T

N i M ir ;i ÞÞ

Twu Alpha function for Peng–

Robinson correction for Eq. (6)

Li, M i, N i = Parameters of pure ith

substance (see details in Honeywell

(2010b))

Eq. (9) H H IDRT ¼ Z 1

121:5bRT

a T dadT

ln

V þð20:5þ1Þb

V þð20:51Þb

Enthalpy equation H = predicted enthalpy

H ID = reference enthalpy evaluated

at 25 C and 1.01 bar

Eq. (10) S S IDR ¼ lnð Z bÞ lnðP =P

Þ A21:5bRT

T a

dadT

ln

V þð20:5þ1Þb

V þð20:51Þb

Entropy equation S = predicted entropy

S ID = reference entropy evaluated at

25 C and 1.01 bar

P pressure in the reference state

(1.01 bar)

Eq. (11) ln/i ¼ ln Z PbRT

þ ð Z 1Þ bib

a21:5bRT

1a 2a

0:5i

PN j¼1 x ja

0:5 j ð1 kijÞ

bib

ln V þð20:5 þ1Þb

V þð20:5 1Þb

Evaluation of fugacity coefficient / = mixture fugacity coefficient of

for the ith component


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4. Conclusions

In the present work a quantitative methodology was developed

for the performance analysis of the vegetable oil refining process.

An advanced thermodynamic model was implemented in order

to reproduce the vapor/liquid equilibrium of crude vegetable oil –

residual solvent system. The model was validated against available

experimental data and was implemented in the refining processsimulator, developed on the Honeywell UniSim Design software.

The simulator allowed for a detailed performance analysis of

the process. The results were compared with field data obtained

from an actual vegetable oil refinery showing good agreement in

reproducing the refining process in the reference conditions.

The effect of the residual solvent content increase on the pro-

cess efficiency was investigated, determining the most significant

nodes of solvent accumulation among the plant process operations

and evaluating its influence on the global energy requirements. In

particular, the ejector systems, aimed at keeping vacuum operating

conditions, were deeply investigated, evaluating the utility con-

sumption increment. Both motive steam and cooling water for con-

densers were analyzed by varying the residual hexane content in

the input crude oil and determining the modification in the opera-

tive conditions for minimizing the energy costs. The study evi-

denced the criticalities related to the management of inlet crude

oil quality, in terms of residual solvent content control, for the

enhancement of the global process efficiency.

Finally, the simulator also allowed investigating the potential

hazards due to formation of flammable mixtures inside the process

vent lines, in presence of purged hexane vapors and air entrained

by gaskets and/or seals of vacuum operating pipelines. The results

evidenced the conditions in which flammable mixtures might

potentially be formed inside the process vents, with fire and explo-

sion hazards in presence of accidental ignition.

Acknowledgement

The authors gratefully acknowledge financial support received

from Regione Toscana (Bando Unico R&S n.2009DUA/526090469/

1).

Appendix A

The present section provides details on the thermodynamic

model implemented in Unisim Design (Honeywell, 2010a,b).

The selected model is based on the Peng–Robinsonequations (Peng

and Robinson, 1976) corrected with the Twu Alpha function (Twu

et al., 1995; Honeywell, 2010b), which takes into account the ex-

cess free energy in order to have more accurate prediction of vapor

pressure. Table A1 summarizes the key parameters and equations

used to predict enthalpy, entropy, the fugacity coefficients for each

component of the mixture and thus the vapor/liquid equilibrium.

Tables A2 and A3 report the specific parameters selected for each

substance considered in the present study.

Appendix B

Table B1 reports the results of the process optimization and

sensitivity analysis, comparing the baseline case results (BC) and

the optimized cases (OCs) by varying the residual hexane content

(HEX in the following, expressed in % by weight basis) up to one

order of magnitude respect to the BC, which features HEX = 0.1%.

The first column of the table reports the process variable of

interest (EJ: ejector, MS: motive steam, CW: cooling water, see

Figs. 4 and 5). The second column report the results obtained for

the baseline case with HEX = 0.1%, while the third column shows

the correspondent optimization of process variables aimed at

Table A3

Determination of system specific binary interaction factor ki, j (i: columns; j: rows) (see Eq. (11) in Table A1).

ki, j i ? j; Triolein Oleic acid n-Hexane n-C29H60 Sterols Tocopherols Water

Triolein – 0 0.095 0 0 0 0

Oleic acid 0 – 0 0 0 0 0

n-Hexane 0.095 0 – 0.031 0 0 0.48

n-C29H60 0 0 0.031 – 0 0 0.48

Sterols 0 0 0 0 – 0 0

Tocopherols 0 0 0 0 0 – 0

Water 0 0 0.48 0.48 0 0 –

Table A2

Main parameters selected for the present analysis (Honeywell, 2010b). For parameters definition see Table A1.

Parameter (see Table A1) Equation (see Table A1) Units (SI) Assigned parameter for each component – Unisim Design library

Triolein Oleic acid n-Hexane n-C29H60 Sterols Tocopherols Water

T c ,i 5 C 680.9 496.9 234.7 564.9 668.1 646.7 374.1

P c ,i 5 kPa 360.2 1390 3032 826 999.7 945.9 22,120

Li 8 – –a 0.7760 0.1363 0.3688 –a –a 0.3831

M i 8 – –a 0.8235 0.8620 0.8247 –a –a 0.8701

N i 8 – –a 0.8235 0.8620 0.8247 –a –a 0.8701

L0 see note (a) – 0.1253 – – – 0.1253 0.1253 –

M0 see note (a) – 0.9118 – – – 0.9118 0.9118 –

N0 see note (a) – 1.9482 – – – 1.9482 1.9482 –

L1 see note (a) – 0.5116 – – – 0.5116 0.5116 –

M1 see note (a) – 0.7841 – – – 0.7841 0.7841 –

N1 see note (a) – 2.8125 – – – 2.8125 2.8125 –

xi see note (a) – 1.6862 – – – 0.9863 0.9624 –

a

The parameters Li, M i and N i depend on individual compounds and were retrieved from UniSim

Design library for the application of Eq. (8) of Table A1. Nevertheless, fornon-library compounds, the Twu alpha function can be estimated by the following expressions: ai ¼ a

ð0Þi ðT Þ þ xiða

ð1Þi ðT Þ a

ð0Þi ðT ÞÞ where a

ð0Þi ¼T

N 0=ðM 01Þr ;i

expðL0ð1 T N 0M 0r ;i ÞÞ; að1Þi ¼ T

N 1=ðM 11Þr ;i expðL1ð1 T

N 1M 1r ;i ÞÞ; T r ;i ¼ T =T c ;i .

In this case, Table A2 reports the relevant parameters for the estimation of the Twu alpha function (L0, M0, N0, L1, M1, N1 and xi).


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keeping the same operative condition in process equipment. The

other column of the table shows the results in case of higher

HEX values. In particular, the third column shows the variationof the process variables able to restore the normal operative condi-

tions in presence of HEX = 0.5%, while the fourth column reports

the correspondent optimized process variables and operative con-

ditions. The same type of results are shown in the fifth and sixth

column for HEX = 1.0%.

Appendix C. Supplementary material

Supplementary data associated with this article can be found, in

the online version, at http://dx.doi.org/10.1016/j.jfoodeng.2013.

01.034.

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EJ3c operative pressure (kPa) 20.0 11.0 20.0 12.0 20.0 12.0

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a Respect to the base case.


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Analysis and Simulation of Vegetable Oil Refining Landucci_pannocchia_pelagagge_nicolella_2013